Computational Genomics (KIZ, Fall 2024)

Computational Genomics Sept, Oct & Nov of 2024 Guest Instructor: Weigang Qiu, Ph.D.
Professor, Department of Biological Sciences, City University of New York, Hunter College & Graduate Center
Adjunct Faculty, Department of Physiology and Biophysics, Institute for Computational Biomedicine, Weil Cornell Medical College Office: B402 Belfer Research Building, 413 East 69th Street, New York, NY 10021, USA Email: wqiu@hunter.cuny.edu Lab Website: https://wiki.genometracker.org

Host: Dr Yun Gao, Ph.D.
Kunming Institute of Zoology (KIZ)

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Course Overview

Welcome to BioMedical Genomics, a computer workshop for advanced undergraduates and graduate students. A genome is the total genetic content of an organism. Driven by breakthroughs such as the decoding of the first human genome and next-generation DNA -sequencing technologies, biomedical sciences are undergoing a rapid and irreversible transformation into a highly data-intensive field.

Genome information is revolutionizing virtually all aspects of life sciences including basic research, medicine, and agriculture. Meanwhile, use of genomic data requires life scientists to be familiar with concepts and skills in biology, computer science, as well as data analysis.

This workshop is designed to introduce computational analysis of genomic data through hands-on computational exercises, using published studies.

The pre-requisites of the course are college-level courses in molecular biology, cell biology, and genetics. Introductory courses in computer programming and statistics are preferred but not strictly required.

Learning goals

By the end of this course successful students will be able to:

• Describe next-generation sequencing (NGS) technologies & contrast it with traditional Sanger sequencing
• Explain applications of NGS technology including pathogen genomics, cancer genomics, human genomic variation, transcriptomics, meta-genomics, epi-genomics, and microbiome.
• Visualize and explore genomics data using RStudio
• Replicate key results using a raw data set produced by a primary research paper

Web Links

• Install R base: https://cloud.r-project.org
• Install R Studio (Desktop version): http://www.rstudio.com/download
• Download: R datasets
• A reference book: R for Data Science (Wickharm & Grolemund)

Assignments, Quizzes, and Final Report

Student performance will be evaluated by attendance, three (3) quizzes, six (6) assignments, and a final report:

• Attendance & participation: 30 pts
• Assignments: 6 x 10 = 60 pts
• Open-Book Quizzes: 3 x 20 pts = 60 pts
• Final presentation: 50 pts

Total: 200 pts

Course Schedule

Week 1, Tuesday, Sep 24, 2024

• Computer setup: Linux terminals
• Linux Tutorial: Linux commands
• Assignment 1.

Week 2, Tuesday, Oct 01, 2024

• Computer setup: conda; jupyter-notebook
• Python Tutorial 1: Basic Python
• Assignment 2

Week 3, Tuesday, Oct 08, 2024

• Quiz #1
• Python Tutorial 2: Advanced Python
• Assignment 3

Week 4, Tuesday, Oct 15, 2024

• Python Tutorial 3: Regular expression & scientific computing with Python
• Assignment 4

Week 5, Tuesday, Oct 22, 2024

• Quiz #2
• Computer setup: R & RStudio
• R Tutorial 1: Basic R
• Assignment 5

Week 6, Tuesday, Oct 29, 2024

• R Tutorial 2: Data visualization & basic statistics
• Assignment 6

Week 7, Tuesday, Nov 05, 2024

• Quiz #3
• Genomics Tutorial 1: Cluster analysis & scRNA analysis
• Final report (draft 1: Background, Hypothesis, Significance, Material & Methods)

Week 8, Tuesday, Nov 12, 2024

• Genomics Tutorial 2. NGS data analysis
• Final report (draft 2: Results & Discussion)

Week 9, Tuesday, Nov 19, 2024

• Genomics Tutorial 3. Monte Carlo simulations of genome evolution
• Final report (draft 3: Conclusions, future directions, reference; Due Nov 26)